Abstract [en]

In this thesis a filter for attitude estimation using sensor fusion of a Star Tracker and a Gyroscope are designed and implemented for integration on the European Data Relay satellite, EDRS. The performance of three filters, Multiplicative Extended Kalman Filter, Unscented Kalman Filter and Particle filter, are evaluated in terms of attitude error, covariance convergence and change of attitude knowledge uncertainty. The filters show similar performance on all three measures and the comparison becomes a question of implementation and computational load. The Multiplicative Extended Kalman Filter is better in both criteria and are chosen for integration on board.